{"id":"W2996871526","doi":"10.1029/2018wr024542","title":"Snowmelt Detection with Calibrated, Enhanced‐Resolution Brightness Temperatures (CETB) in Colorado Watersheds","year":2020,"lang":"en","type":"article","venue":"Water Resources Research","topic":"Cryospheric studies and observations","field":"Earth and Planetary Sciences","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria","funders":"","keywords":"Snowmelt; Snowpack; Environmental science; Snow; Terrain; Meltwater; Remote sensing; Meteorology; Hydrology (agriculture); Geology; Geography","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003181933,0.0001432881,0.0002194165,0.0006831094,0.0003041336,0.0004483329,0.0002609568,0.0002471565,0.0003276221],"category_scores_gemma":[0.0008671473,0.0001916168,0.0001061887,0.0007068655,0.0001614682,0.0003086207,0.000280463,0.0001849794,0.00008913488],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007509062,"about_ca_system_score_gemma":0.0003024931,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.08511655,"about_ca_topic_score_gemma":0.1815286,"domain_scores_codex":[0.9997923,0.00003693312,0.000008685893,0.00008792089,0.00005200712,0.00002221644],"domain_scores_gemma":[0.9995178,0.00008011017,0.0001026117,0.00004389516,0.0002186835,0.00003695645],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002555251,0.0001432703,0.9407656,0.00003406407,0.00006556718,0.0001288206,0.0004096642,0.006049495,0.0309852,0.00007996623,0.0005140776,0.02056871],"study_design_scores_gemma":[0.00002154764,0.00004227829,0.966844,0.000009175266,0.00001946762,0.00004408771,0.0002007384,0.02741334,0.004599555,0.00003199705,0.0007635723,0.00001026921],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9982141,0.00004289556,0.0007177999,0.00002149245,0.00000140379,0.00001164476,0.0003844963,0.00004575237,0.0005604543],"genre_scores_gemma":[0.9973303,0.00002409367,0.001811495,0.000007982777,0.000002690134,0.00001207259,0.0006528626,0.00000618109,0.0001523438],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.08511655,"threshold_uncertainty_score":0.1692423,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04264606931242657,"score_gpt":0.2562189910933561,"score_spread":0.2135729217809295,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}